RESOURCES

Machine-Learning-Tokyo/DL-workshop-series

DL-workshop-series Code used for Deep Learning related workshops for Machine Learning Tokyo (MLT) Part I: Convolution Operations Implementation ConvKernels: colab notebook with simple examples of various kernels applied on an image using convolution operationConvNets: colab notebook with functions for constructing keras models. Models: AlexNetVGGInceptionMobileNetShuffleNetResNetDenseNetXceptionUnetSqueezeNetYOLORefineNet Slides Link to the presentation: https://drive.google.com/open?id=1sXztx3E9M3G0BIRLh6sxaqVOEOdJVJTrzHOixA5b-rM ...
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Great R packages by Sharon Machlis

Great R packages for data import, wrangling and visualization One of the great things about R is the thousands of packages users have written to solve specific problems in various disciplines -- analyzing everything from weather or financial data to the human genome -- not to mention analyzing computer security-breach data. [ Need to learn R or ...
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A Biologist’s Guide to Mathematical Modeling in Ecology and Evolution

Thirty years ago, biologists could get by with a rudimentary grasp of mathematics and modeling. Not so today. In seeking to answer fundamental questions about how biological systems function and change over time, the modern biologist is as likely to rely on sophisticated mathematical and computer-based models as traditional fieldwork ...
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Model-based Inference

ICTP Workshop on Mathematical Models of Climate Variability, Environmental Change and Infectious Diseases 8–19 May 2017 Instructor Prof. Aaron A. King, Ph.D. Departments of Ecology & Evolutionary Biology and Mathematics University of Michigan Email: kingaaictp5@gmail.com Preparing for the workshop Complete the R tutorial before the beginning of the course. If you wish to use your ...
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Introduction to R

A Tutorial Introduction to R Aaron A. King, Stu Field, Ben Bolker, Steve Ellner 1 How to use this document 2 What is R ? 3 Getting started with R 3.1 Installing R on your computer 3.2 Starting R 3.3 Stopping R 4 Interactive calculations 5 The help system 6 A first interactive session 6.1 Descriptive statistics 6.2 Linear regression 7 Statistics in R 8 The R package system 9 Data structures in R 9.1 Vectors ...
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